Triple
T13194686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comte de Mortsauf |
E314080
|
entity |
| Predicate | impactOnFamily |
P108983
|
FINISHED |
| Object | causes suffering to his wife |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: causes suffering to his wife | Statement: [Comte de Mortsauf, impactOnFamily, causes suffering to his wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnFamily Context triple: [Comte de Mortsauf, impactOnFamily, causes suffering to his wife]
-
A.
familyAspect
Indicates a relationship where one entity is characterized by a particular familial role, status, or aspect in relation to another entity.
-
B.
familyInvolvement
Indicates that there is participation, engagement, or influence of family members in the context of a particular activity, decision, or situation.
-
C.
family
Indicates a familial relationship or connection between entities, such as being related by blood, marriage, or adoption.
-
D.
interFamilyRelations
Indicates relationships or interactions that occur between different families or family units.
-
E.
supportedFamilyLifeOf
Indicates that one entity provided assistance or resources that helped sustain or improve the family life or family-related well-being of another entity.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:16 p.m.